From FDE to AFDE

I. The Productivity Ceiling

Every new product brings the same inevitable question: how long until it’s ready to release? It’s a simple question on the surface, but at its heart sits a fundamental tension: speed of development vs. quality of development.

Think of the decision like a chart of productivity. Speed is on the y-axis and quality on the x-axis. The curve bows outward. You can have moderate amounts of both, but at the extremes the trade-off becomes punishing. Inherently, there is a maximum productivity that can be achieved without changing underlying variables: talent, tooling, process, or environment.

The productivity ceiling. Every organization picks a point along the curve: pure speed, pure quality, or somewhere in between. Agentic development pushes the ceiling outward.

II. Four Levers: A Golf Analogy

I find golf to be an easy analogy here. Think of your organization as a professional golfer and your productivity as golf score.

1. Talent: Better players have better scores. No sugarcoating this one: an organization is the sum of its parts, and talent is objective.
2. Tooling: Modern equipment makes the ball go farther and straighter. Frontier AI models and agentic development tooling have resulted in higher quality code faster — a true game changer.
3. Process: Professional golfers use a range finder to find distance, consult their caddy, and take a practice swing all before actually taking a shot. Software development requires careful thought, collaboration, and planning before any code is written.
4. Environment: Strategy and scores differ depending on the difficulty of the course, weather, etc. The composition of a codebase and the quality of a dev environment impact the quality of code written.

Historically, raising the ceiling of productivity meant pulling these levers one at a time. You hired a better engineer, adopted a new tool, tightened your process, or cleaned up your codebase. Each change was only marginally additive.

III. The Compounding Effect

When deployed effectively, agentic development changes that math. It collapses the tooling stack into something faster and more capable, absorbing process grunt work so that high-judgment tasks receive more attention. This in turn raises the effective skill of every engineer on the team and allows a small team to navigate, refactor, and maintain a codebase that previously would have demanded twice the headcount. The four levers can now be moved together, resulting in a compounding, rather than merely additive, effect.

IV. The Rise of the Forward Deployed Engineer

This then begs the question: how does an organization unlock agentic development? In response, the market for FDEs (Forward Deployed Engineers) has exploded. Organizations that lack the expertise are turning to industry experts who advise them on this new path.

FDEs install tooling and processes that optimize both speed and quality by leveraging the latest frontier AI models.

The FDE model works. Just look at the success of Palantir alongside the new enterprise AI services ventures from Anthropic and OpenAI. But is it optimized? It requires massive capital expenditure, and when the engagement ends, the expertise walks out the door. Still, the agentic development space continues to evolve rapidly. FDEs install tooling and processes optimized for today, but environments slowly degrade without the expertise to maintain them as best practices change and new code is written. The compounding effect is lost.

V. Autonomous Forward Deployed Engineers

So the next step is clear: FDEs must remain in place to avoid losing expertise or degrading the environment. The economics of keeping a human FDE on retainer indefinitely are out of reach for most organizations. This is where Autonomous Forward Deployed Engineers come in. An AFDE is an AI agent that lives inside your codebase and tooling, continuously maintaining and evolving your environment as the frontier shifts and your software grows.

Unlike their human counterparts, AFDEs don’t churn. They stay current with best practices automatically, integrate directly into your tooling and repo, and operate continuously, which means the compounding effect doesn’t decay the moment an engagement ends. And they do it at a price point that finally makes the math work.

Karya is building autonomous forward deployed engineers, making the compounding effects of agentic development accessible to every organization, not just the few that can afford to rent the expertise. The ceiling on productivity is still there. We just made it a lot cheaper to push through it.